利用codebook法训练得到背景模型后，对背景差分得到的掩模图像去噪声并找到较大连通域。相对于平均背景法，它的分割效果更好些。当然，分割效果和背景模型训练的帧数有很大关系，适当调整一些参数会得到更好的效果。
1 #include "stdafx.h"
2 #include "cv.h"
3 #include "highgui.h"
4
5 #define CHANNELS 3
6 typedef struct ce{
7 uchar learnHigh[CHANNELS];
8 uchar learnLow[CHANNELS];
9 uchar max[CHANNELS];
10 uchar min[CHANNELS];
11 int t_last_update;
12 int stale;
13 }code_element;
14
15 typedef struct code_book{
16 code_element **cb;
17 int numEntries;
18 int t;
19 }codeBook;
20
21 #define CVCONTOUR_APPROX_LEVEL 2 // Approx.threshold - the bigger it is, the simpler is the boundary
22 #define CVCLOSE_ITR 1 // How many iterations of erosion and/or dialation there should be
23
24 #define CV_CVX_WHITE CV_RGB(0xff,0xff,0xff)
25 #define CV_CVX_BLACK CV_RGB(0x00,0x00,0x00)
26
27 ///////////////////////////////////////////////////////////////////////////////////
28 // int updateCodeBook(uchar *p, codeBook &c, unsigned cbBounds)
29 // Updates the codebook entry with a new data point
30 //
31 // p Pointer to a YUV pixel
32 // c Codebook for this pixel
33 // cbBounds Learning bounds for codebook (Rule of thumb: 10)
34 // numChannels Number of color channels we‘re learning
35 //
36 // NOTES:
37 // cvBounds must be of size cvBounds[numChannels]
38 //
39 // RETURN
40 // codebook index 更新码本
41 int update_codebook(uchar* p,codeBook &c, unsigned* cbBounds, int numChannels)
42 {
43 if(c.numEntries==0)c.t=0; //码本中码元数为0初始化时间为0
44 c.t+=1; //每调用一次时间数加1
45
46 int n;
47 unsigned int high[3],low[3];
48 for(n=0;n<numChannels;n++)
49 {
50 //加减cbBonds作为此像素阈值上下界
51 high[n]=*(p+n) + *(cbBounds+n); //直接使用指针操作更快
52 if(high[n]>255) high[n]=255;
53 low[n]=*(p+n)-*(cbBounds+n);
54 if(low[n]<0) low[n]=0;
55 }
56
57 int matchChannel;
58 int i;
59 for(i=0;i<c.numEntries;i++)
60 {
61 matchChannel=0;
62 for(n=0;n<numChannels;n++)
63 {
64 if((c.cb[i]->learnLow[n]<=*(p+n)) && (*(p+n)<=c.cb[i]->learnHigh[n]))
65 {
66 matchChannel++;
67 }
68 }
69 if(matchChannel==numChannels)
70 {
71 c.cb[i]->t_last_update=c.t; //更新码元时间
72 for(n=0;n<numChannels;n++) //调整码元各通道最大最小值
73 {
74 if(c.cb[i]->max[n]<*(p+n))
75 c.cb[i]->max[n]=*(p+n);
76 else if(c.cb[i]->min[n]>*(p+n))
77 c.cb[i]->min[n]=*(p+n);
78 }
79 break;
80 }
81 }
82
83 //像素p不满足码本中任何一个码元,创建一个新码元
84 if(i == c.numEntries)
85 {
86 code_element **foo=new code_element*[c.numEntries+1];
87 for(int ii=0;ii<c.numEntries;ii++)
88 foo[ii]=c.cb[ii];
89 foo[c.numEntries]=new code_element;
90 if(c.numEntries)delete[]c.cb;
91 c.cb=foo;
92 for(n=0;n<numChannels;n++)
93 {
94 c.cb[c.numEntries]->learnHigh[n]=high[n];
95 c.cb[c.numEntries]->learnLow[n]=low[n];
96 c.cb[c.numEntries]->max[n]=*(p+n);
97 c.cb[c.numEntries]->min[n]=*(p+n);
98 }
99 c.cb[c.numEntries]->t_last_update = c.t;
100 c.cb[c.numEntries]->stale = 0;
101 c.numEntries += 1;
102 }
103
104 //计算码元上次更新到现在的时间
105 for(int s=0; s<c.numEntries; s++)
106 {
107 int negRun=c.t-c.cb[s]->t_last_update;
108 if(c.cb[s]->stale < negRun)
109 c.cb[s]->stale = negRun;
110 }
111
112 //如果像素通道值在高低阈值内,但在码元阈值之外,则缓慢调整此码元学习界限(max,min相当于外墙,粗调;learnHigh,learnLow相当于内墙,细调)
113 for(n=0; n<numChannels; n++)
114 {
115 if(c.cb[i]->learnHigh[n]<high[n])
116 c.cb[i]->learnHigh[n]+=1;
117 if(c.cb[i]->learnLow[n]>low[n])
118 c.cb[i]->learnLow[n]-=1;
119 }
120
121 return i;
122 }
123
124 // 删除一定时间内未访问的码元,避免学习噪声的codebook
125 int cvclearStaleEntries(codeBook &c)
126 {
127 int staleThresh=c.t>>1; //设定刷新时间
128 int *keep=new int[c.numEntries];
129 int keepCnt=0; //记录不删除码元码元数目
130 for(int i=0; i<c.numEntries; i++)
131 {
132 if(c.cb[i]->stale > staleThresh)
133 keep[i]=0; //保留标志符
134 else
135 {
136 keep[i]=1; //删除标志符
137 keepCnt+=1;
138 }
139 }
140
141 c.t=0;
142 code_element **foo=new code_element*[keepCnt];
143 int k=0;
144 for(int ii=0; ii<c.numEntries; ii++)
145 {
146 if(keep[ii])
147 {
148 foo[k]=c.cb[ii];
149 foo[k]->stale=0; //We have to refresh these entries for next clearStale
150 foo[k]->t_last_update=0;
151 k++;
152 }
153 }
154
155 delete[] keep;
156 delete[] c.cb;
157 c.cb=foo;
158 int numCleared=c.numEntries-keepCnt;
159 c.numEntries=keepCnt;
160 return numCleared; //返回删除的码元
161 }
162
163 ///////////////////////////////////////////////////////////////////////////////////
164 // uchar cvbackgroundDiff(uchar *p, codeBook &c, int minMod, int maxMod)
165 // Given a pixel and a code book, determine if the pixel is covered by the codebook
166 //
167 // p pixel pointer (YUV interleaved)
168 // c codebook reference
169 // numChannels Number of channels we are testing
170 // maxMod Add this (possibly negative) number onto max level when code_element determining if new pixel is foreground
171 // minMod Subract this (possible negative) number from min level code_element when determining if pixel is foreground
172 //
173 // NOTES:
174 // minMod and maxMod must have length numChannels, e.g. 3 channels => minMod[3], maxMod[3].
175 //
176 // Return
177 // 0 => background, 255 => foreground 背景差分,寻找前景目标
178 uchar cvbackgroundDiff(uchar *p, codeBook &c, int numChannels, int *minMod, int *maxMod)
179 {
180 int matchChannel;
181 int i;
182 for(i=0; i<c.numEntries; i++)
183 {
184 matchChannel=0;
185 for(int n=0; n<numChannels; n++)
186 {
187 if((c.cb[i]->min[n]-minMod[n]<=*(p+n)) && (*(p+n)<=c.cb[i]->max[n]+maxMod[n]))
188 matchChannel++;
189 else
190 break;
191 }
192 if(matchChannel==numChannels)
193 break;
194 }
195 if(i==c.numEntries) //像素p各通道值不满足所有的码元,则为前景,返回白色
196 return 255;
197 return 0; //匹配到一个码元时,则为背景,返回黑色
198 }
199
200 ///////////////////////////////////////////////////////////////////////////////////////////
201 //void cvconnectedComponents(IplImage *mask, int poly1_hull0, float perimScale, int *num, CvRect *bbs, CvPoint *centers)
202 // This cleans up the foreground segmentation mask derived from calls to cvbackgroundDiff
203 //
204 // mask Is a grayscale (8 bit depth) "raw" mask image which will be cleaned up
205 //
206 // OPTIONAL PARAMETERS:
207 // poly1_hull0 If set, approximate connected component by (DEFAULT) polygon, or else convex hull (0)
208 // perimScale Len = image (width+height)/perimScale. If contour len < this, delete that contour (DEFAULT: 4)
209 void cvconnectedComponents(IplImage *mask, int poly1_hull0, float perimScale)
210 {
211 static CvMemStorage* mem_storage=NULL;
212 static CvSeq* contours=NULL;
213 cvMorphologyEx( mask, mask, NULL, NULL, CV_MOP_OPEN, CVCLOSE_ITR);
214 cvMorphologyEx( mask, mask, NULL, NULL, CV_MOP_CLOSE, CVCLOSE_ITR);
215
216 if(mem_storage==NULL)
217 mem_storage=cvCreateMemStorage(0);
218 else
219 cvClearMemStorage(mem_storage);
220
221 CvContourScanner scanner=cvStartFindContours(mask,mem_storage,sizeof(CvContour),CV_RETR_EXTERNAL);
222 CvSeq* c;
223 int numCont=0; //轮廓数
224 while((c=cvFindNextContour(scanner))!=NULL)
225 {
226 double len=cvContourPerimeter(c);
227 double q=(mask->height+mask->width)/perimScale; //轮廓长度阀值设定
228 if(len<q)
229 cvSubstituteContour(scanner,NULL); //删除太短轮廓
230 else
231 {
232 CvSeq* c_new;
233 if(poly1_hull0) //用多边形拟合轮廓
234 c_new = cvApproxPoly(c, sizeof(CvContour), mem_storage,
235 CV_POLY_APPROX_DP, CVCONTOUR_APPROX_LEVEL);
236 else //计算轮廓Hu矩
237 c_new = cvConvexHull2(c,mem_storage, CV_CLOCKWISE, 1);
238
239 cvSubstituteContour(scanner,c_new); //替换拟合后的多边形轮廓
240 numCont++;
241 }
242 }
243 contours = cvEndFindContours(&scanner); //结束扫描,并返回最高层的第一个轮廓指针
244
245 cvZero(mask);
246 for(c=contours; c!=NULL; c=c->h_next)
247 cvDrawContours(mask,c,CV_CVX_WHITE, CV_CVX_BLACK,-1,CV_FILLED,8);
248 }
249
250 int main()
251 {
252 ///////////////////////////////////////
253 // 需要使用的变量
254 CvCapture* capture=NULL;
255 IplImage* rawImage=NULL; //视频的每一帧原图像
256 IplImage* yuvImage=NULL; //比经验角度看绝大部分背景中的变化倾向于沿亮度轴,而不是颜色轴,故YUV颜色空间效果更好
257 IplImage* ImaskCodeBook=NULL; //掩模图像
258 IplImage* ImaskCodeBookCC=NULL; //清除噪声后并采用多边形法拟合轮廓连通域的掩模图像
259
260 codeBook* cB=NULL;
261 unsigned cbBounds[CHANNELS];
262 uchar* pColor=NULL; //yuvImage像素指针
263 int imageLen=0;
264 int nChannels=CHANNELS;
265 int minMod[CHANNELS];
266 int maxMod[CHANNELS];
267
268 //////////////////////////////////////////////////////////////////////////
269 // 初始化各变量
270 cvNamedWindow("原图");
271 cvNamedWindow("掩模图像");
272 cvNamedWindow("连通域掩模图像");
273
274 //capture = cvCreateFileCapture("C:/Users/shark/Desktop/eagle.flv");
275 capture=cvCreateCameraCapture(0);
276 if(!capture)
277 {
278 printf("Couldn‘t open the capture!");
279 return -1;
280 }
281
282 rawImage=cvQueryFrame(capture);
283 int width=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH);
284 int height=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT);
285 CvSize size=cvSize(width,height);
286 yuvImage=cvCreateImage(size,8,3);
287 ImaskCodeBook = cvCreateImage(size, IPL_DEPTH_8U, 1);
288 ImaskCodeBookCC = cvCreateImage(size, IPL_DEPTH_8U, 1);
289 cvSet(ImaskCodeBook,cvScalar(255));
290
291 imageLen=width*height;
292 cB=new codeBook[imageLen]; //得到与图像像素数目长度一样的一组码本,以便对每个像素进行处理
293
294 for(int i=0;i<imageLen;i++)
295 cB[i].numEntries=0;
296 for(int i=0;i<nChannels;i++)
297 {
298 cbBounds[i]=10;
299 minMod[i]=20; //用于背景差分函数中
300 maxMod[i]=20; //调整其值以达到最好的分割
301 }
302
303 //////////////////////////////////////////////////////////////////////////
304 // 开始处理视频每一帧图像
305 for(int i=0;;i++)
306 {
307 if(!(rawImage=cvQueryFrame(capture)))
308 break;
309 cvCvtColor(rawImage, yuvImage, CV_BGR2YCrCb);
310 // 色彩空间转换,将rawImage 转换到YUV色彩空间,输出到yuvImage
311 // 即使不转换效果依然很好
312 // yuvImage = cvCloneImage(rawImage);
313
314 if(i<=30) //前30帧进行背景学习
315 {
316 pColor=(uchar*)yuvImage->imageData;
317 for(int c=0; c<imageLen; c++)
318 {
319 update_codebook(pColor, cB[c], cbBounds, nChannels); //对每个像素调用此函数
320 pColor+=3;
321 }
322 if(i==30)
323 {
324 for(int c=0;c<imageLen;c++)
325 {
326 cvclearStaleEntries(cB[c]); //第30时帧时,删除每个像素码本中陈旧的码元
327 }
328 }
329 }
330 else
331 {
332 uchar maskPixel;
333 pColor=(uchar*)yuvImage->imageData;
334 uchar* pMask=(uchar*)ImaskCodeBook->imageData;
335 for(int c=0;c<imageLen;c++)
336 {
337 maskPixel=cvbackgroundDiff(pColor,cB[c],nChannels,minMod,maxMod);
338 *pMask++=maskPixel;
339 pColor+=3;
340 }
341 cvCopy(ImaskCodeBook,ImaskCodeBookCC);
342 cvconnectedComponents(ImaskCodeBookCC,1,4.0);
343 cvShowImage("掩模图像",ImaskCodeBook);
344 cvShowImage("连通域掩模图像",ImaskCodeBookCC);
345 }
346 cvShowImage("原图",rawImage);
347 if (cvWaitKey(30) == 27)
348 break;
349 }
350
351 cvReleaseCapture(&capture);
352 if (yuvImage)
353 cvReleaseImage(&yuvImage);
354 if(ImaskCodeBook)
355 cvReleaseImage(&ImaskCodeBook);
356 cvDestroyAllWindows();
357 delete [] cB;
358
359 return 0;
360
361 }
时间： 2024-08-17 01:17:35